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17 Kasım 2022 Perşembe

Creating tables for model comparison

In this post, I will compile codes to compare different models' results. The post will hopefully lengthen as I add new ones..

Here is the first one comparing a decision tree, rf, and other tuned regressors:

The code creates this table:

Code:

models_test_comp_df = pd.concat(
[
dt_regressor_perf_test.T,
regressor_perf_test.T,
bagging_estimator_perf_test.T,
dtree_tuned_regressor_perf_test.T,
bagging_tuned_regressor_perf_test.T,
rf_tuned_regressor_perf_test.T
],
axis=1,
)
models_test_comp_df.columns = [
"Decision tree regressor",
"Random Forest regressor",
"Bagging regressor",
"Tuned Decision Tree regressor",
"Tuned Bagging Tree regressor",
"Tuned Random Forest Regressor"]
print("Test performance comparison:")
models_test_comp_df

A second code to retrieve a table for a similar comparison: (table not included this time)

# defining list of models you have trained
models = [lr, dtree, ridge_model, dtree_tuned, rf_model, rf_model_tuned]
# defining empty lists to add train and test results
r2_train = []
r2_test = []
rmse_train= []
rmse_test= []
# looping through all the models to get the rmse and r2 scores
for model in models:
# accuracy score
j = get_model_score(model,False)

r2_train.append(j[0])
r2_test.append(j[1])
rmse_train.append(j[2])
rmse_test.append(j[3])
-------
comparison_frame = pd.DataFrame({'Model':['Linear Regression','Decision Tree','Ridge Model','Tuned Decision Tree','Random Forest','Tuned Random Forest'],
'Train_r2': r2_train,'Test_r2': r2_test,
'Train_RMSE':rmse_train,'Test_RMSE':rmse_test})
comparison_frame

4 Kasım 2022 Cuma

Three SQL Game Web Sites

1. SQL Murder Mystery: Using SQL knowledge to find a killer in SQL city. https://mystery.knightlab.com

2. SQL Police Department: You are joining SQLPD, and solving crimes while learning SQL. https://sqlpd.com

3. Schemaverse: A space-based strategy game implemented entirely within a PostgreSQL database. You will be commanding your fleet and competing against other players using raw SQL commands. https://schemaverse.com